AI Leaders: Who They Are and How They Operate

Only 15% of the organizations surveyed were classified as "AI leaders." These companies stand out for their clear strategies, mature operating models, and focused execution. But above all, the numbers speak for themselves: AI leaders are 2.5 times more likely to achieve revenue growth above 10% and over 3.6 times more likely to reach profit margins of 15% or higher.

In Europe, these figures are even more pronounced: the likelihood of growth above 10% rises to 2.9 times compared to other organizations. A competitive gap that is rapidly widening and risks leaving behind those who have not yet embarked on a structured AI transformation journey.

The Nine Characteristics of Leaders

The report identifies nine distinctive traits that characterize successful organizations, divided between strategy and execution:

On the strategic front:

•       Strategic alignment and speed: leaders win by closely aligning AI with business strategy, transforming focus and speed into extraordinary financial results.

•       Focused end-to-end approach: top performers concentrate on high-value areas and redesign workflows from start to finish, not limiting themselves to superficial interventions.

•       Flywheel effect: initial investments yield early successes that fuel new reinvestments to support further growth.

•       Core reinvention: leaders rebuild core applications by integrating AI from the ground up, rather than settling for superficial add-ons.

On the execution front:

•       Security at scale: they build scalable and secure stacks, investing in private and sovereign AI infrastructures.

•       AI expert-first: they use AI to amplify the impact of expert professionals, not to replace them.

•       Lasting change: they approach adoption as a business transformation program with constructive change management.

•       Governance for scalability: they centralize governance, formalize enterprise oversight, and appoint dedicated Chief AI Officers.

•       Partner-driven growth: they leverage strategic collaborations and outcome-based profit-sharing models.

The Governance Shift: From CIOs to CEOs

One of the most significant findings from the research concerns AI governance. 78% of AI leaders have a dedicated Chief AI Officer and formal governance structures. However, the most profound change relates to who makes decisions: responsibility for AI now rests with boards of directors and requires an agenda that involves the entire organization.

This trend is also confirmed by the BCG AI Radar 2026, which reports that 72% of CEOs claim to be the primary decision-makers on AI-related choices, a figure that has doubled compared to the previous year. AI is no longer seen as an exclusively technological or IT issue, but as a direct lever of competitiveness, organization, and business model.

"Once AI and business strategies are aligned, the most effective move is to choose one or two areas capable of generating extraordinary value and redesign them end-to-end with AI. Supporting this targeted approach with solid governance, modern infrastructures, and trusted partners is how today's AI leaders are transforming pilot projects into profits."

— Abhijit Dubey, CEO and CAIO of NTT DATA, Inc.

Agentic AI: The New Frontier

A significant part of industry analysis is dedicated to agentic AI, or systems capable of acting with greater autonomy, making operational decisions, and coordinating complex workflows. In 2026, AI agents will be tasked with managing specific activities within existing processes, from ticketing to supply chain, from CRM to application development, without replacing work teams but automating well-defined parts of the workflow.

According to the BCG AI Radar, about 90% of CEOs believe that AI agents will enable the measurement of tangible ROI by 2026, and over 30% of the AI budget planned for next year will be allocated to these solutions. The impact on the organization of work appears significant: within three years, AI will increasingly take on the role of operational assistant, coach, mentor, and, in some cases, supervisor of processes.

Investments in Exponential Growth

Investments in artificial intelligence, calculated as a share of corporate revenues, are set to double in 2026, rising from about 0.8% in 2025 to 1.7% in 2026, after an estimated 0.6% for 2024. This figure spans across sectors: technology, finance, insurance, energy, healthcare, and public administration all show expected increases.

This rise does not appear to be linked to an opportunistic or speculative logic. 94% of CEOs state that they will continue to invest in AI even if the initiatives launched do not yield an immediate return in 2026. Only 6% foresee a downsizing in case of results below expectations. The rest of the sample indicates a tendency towards strategic revision or strengthening of skills.

Security and Risks: The Open Challenges

The increase in the autonomy of AI systems inevitably raises concerns regarding security. 53% of respondents cite data privacy and cybersecurity as the main risk associated with AI. At the same time, new areas of concern are emerging: technological failures, the environmental impact of AI, and geopolitical instability, all increasing as sources of perceived risk.

In the specific case of agentic AI, leaders' opinions are ambivalent: 9% consider it the main threat to cybersecurity, while 32% see it as the greatest opportunity, thanks to its ability to continuously monitor systems and respond more quickly to incidents. The majority, at 59%, interpret it as a combination of risk and opportunity, requiring adaptive governance models.

Geographical Differences: East vs. West

The reports also highlight a significant geographical divide. CEOs in Asia, particularly in India and Greater China, show very high levels of confidence, with optimism about AI payoffs exceeding 70%. In Europe and the UK, confidence remains more subdued and is accompanied by greater competitive pressure, linked to the fear of falling behind.

This difference suggests different decision-making models: value-led in Asia, where AI is adopted because it is perceived as a direct value generator; pressure-led in many Western economies, where adoption also responds to defensive dynamics.

The Italian Context: The National Strategy 2024-2026

The Italian landscape fits into this global context with the Italian Strategy for Artificial Intelligence 2024-2026, which aims to position the country as a key player in the technological transition. The strategy is articulated across four macro areas: Research, Public Administration, Enterprises, and Training.

With Italian universities and the research world ranking seventh globally, the highly competitive entrepreneurial fabric represents fertile ground for AI development. Strategic actions include consolidating the Italian research ecosystem, developing national multimodal models compliant with European regulations, and enhancing dedicated infrastructures.

AI as a Strategic Infrastructure

2026 will be the year when artificial intelligence will definitively cease to be perceived as experimentation and will become strategic infrastructure. As Yutaka Sasaki, President and CEO of NTT DATA Group, effectively summarizes: "Our research shows that a select group of leaders is already using AI to differentiate themselves, grow, and reinvent the way people and machines create value together."

The value of AI will no longer depend solely on the power of the models, but on the organizations' ability to integrate them securely, measurably, and sustainably. The decisive variable will not be so much the technology itself, but the ability of companies to integrate it into processes, decisions, and accountability models.

Companies that can move in this direction will be the first to turn AI into a tangible competitive advantage. For all others, the risk is to remain spectators of a transformation that is redefining the rules of competitive play on a global scale.

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Sources:

•       NTT DATA, "2026 Global AI Report: A Playbook for AI Leaders", December 2025

•       Boston Consulting Group, "BCG AI Radar 2026", January 2026

AgID, "Italian Strategy for Artificial Intelligence 2024